Proceedings. AMIA Symposium最新文献

To address the problem of semantic inconsistencies between medical databases, semantic network representations can be utilized to automate the matching of medical concepts between the databases. The performance of automated concept matching was tested by creating semantic network representations for two laboratory databases, one from a pediatric hospital and the other from an oncology institute. The matching algorithms identified all equivalent concepts that were present in both databases, and did not leave any equivalent concepts unmatched. By automatically identifying semantically equivalent concepts, the Medical Information Acquisition and Transmission Enabler (MEDIATE) facilitates data exchange between heterogeneous systems because no pre-negotiation is required. Consequently, system scalability and stability is improved.

Digital or digitized biomedical images often have very high resolutions', which make them difficult or impossible to display on computer screens. Therefore, it is desirable to develop a multiresolution display method with which users can freely browse the contents of those high resolution images. In this paper, we present an improved wavelet-based progressive image display algorithm by stressing on the encoding and decoding process. The encoder, which dynamically determines levels of transform and partition of coefficients, is based on a modified Haar wavelet transform. The decoder retrieves the necessary data and reconstructs the requested region at a scale specified by the user. A prototype system, which enables virtually any size of images to be displayed progressively, has been implemented based on this algorithm. The system has low computational complexity for both encoding and decoding process.

We present a method to obtain an end-to-end characterization of the performance of an application over a network. This method is not dependent on any specific application or type of network. The method requires characterization of network parameters, such as latency and packet loss, between the expected server or client endpoints, as well as characterization of the application's constraints on these parameters. A subjective metric is presented that integrates these characterizations and that operates over a wide range of applications and networks. We believe that this method may be of wide applicability as research and educational applications increasingly make use of computation and data servers that are distributed over the Internet.

In general, it is very straightforward to store concept identifiers in electronic medical records and represent them in messages. Information models typically specify the fields that can contain coded entries. For each of these fields there may be additional constraints governing exactly which concept identifiers are applicable. However, because modern terminologies such as SNOMED CT are compositional, allowing concept expressions to be pre-coordinated within the terminology or post-coordinated within the medical record, there remains the potential to express a concept in more than one way. Often times, the various representations are similar, but not equivalent. This paper describes an approach for retrieving these pre- and post-coordinated concept expressions: (1) Create concept expressions using a logically-well-structured terminology (e.g., SNOMED CT) according to the rules of a well-specified information model (in this paper we use the HL7 RIM); (2) Transform pre- and post-coordinated concept expressions into a normalized form; (3) Transform queries into the same normalized form. The normalized instances can then be directly compared to the query. Several implementation considerations have been identified. Transformations into a normal form and execution of queries that require traversal of hierarchies need to be optimized. A detailed understanding of the information model and the terminology model are prerequisites. Queries based on the semantic properties of concepts are only as complete as the semantic information contained in the terminology model. Despite these considerations, the approach appears powerful and will continue to be refined.

Computer-based prompting and reminder systems have been shown to be highly effective in increasing rates of preventive services delivery. However, there are many more recommended preventive services than can be practically included in a typical clinic visit. Therefore prioritization of preventive services prompts is necessary. We describe two approaches to prioritizing preventive services prompts based on expected value decision making. One method involves a static, global prioritization across all preventive services and has been used in a production system for almost 7 years. The second method uses influence diagrams to prioritize prompts dynamically, based on individual patient data. The latter approach is still under development. Both methods are labor intensive and require a combination of epidemiologic data and expert judgment. Compromises in strictly normative process were necessary to achieve user satisfaction.

Objective: To identify controlled evidence from the child health literature on patient conditions and clinical procedures that resulted in unacceptable adverse outcomes.

Methods: Systematic searches of MEDLINE (1966 to 2001), and Cochrane Database of Systematic Reviews (2001) were done. Studies that met the eligibility criteria, were verified for quality of methodology and lack of conflicting studies. A knowledge base of Child Health Safety Modules was then developed. The knowledge base could be used to transfer controlled evidence on potentially harmful interventions into clinical decision support systems conforming with Arden Syntax, a widely applied computer standard.

Results: The searches identified knowledge to create 41 Child Health Safety Modules for medications and procedures in child health care, from 29 randomized controlled trials and 12 non-randomized controlled studies. The modules are focused on 28 medication interventions and 13 other clinical procedures. Eighty five percent of the studies were published between 1997-2001.

Conclusion: An increasing amount of controlled evidence on risks of adverse outcomes in child health is available to alert clinicians when potential planning errors are about to be overlooked.

The purpose of this paper is to explore the application of knowledge management concepts to an information systems (IS) knowledge base, as opposed to a clinical one. The field of Medical Informatics is committed to helping others manage medical information and knowledge through the application of information technology. At Partners HealthCare, a wide variety of clinical information management systems have been built and implemented in complex environments, creating an extensive applied informatics knowledge base. How should healthcare IS departments manage this intellectual capital? That's the question that Partners HealthCare is asking its senior and middle IS managers. This paper reports on an internal survey addressing Knowledge Management (KM) requirements, the potential application of this technology in our organization, and discusses where we are today and where to go from here.

Physicians have many unmet information needs that arise in the course of patient care. Many clinical questions could potentially be answered by streamlined access to medical literature, textbooks, and clinical guidelines in the context of the electronic medical record. We designed and implemented SmartQuery, a prototype application to provide context-sensitive links from an electronic patient record to relevant medical knowledge sources, then performed a preliminary user evaluation. Our results suggest that such an application may be clinically useful, and provide some insight into problems and priorities for future development.

The German language and in particular biomedical terms exhibit a rich and productive morphology. Beyond inflection and comparison forms frequently spelling variants, German - Greek/Latin synonyms and nominal compounds exist. For the English language, the SPECIALIST LEXICON, part of the UMLS project, covers a broad range of biomedical terms. In this paper we describe the database model and the functionality of the GERMAN SPECIALIST LEXICON, an ongoing project to develop a lexical resource for German-language medical terminology. Similar to the SPECIALIST LEXICON it is accompanied by tools for the recognition and generation of lexical variants, as well as by databases linking synonymous words, spelling variants, phrases and abbreviations.

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system.